- Genome browsers for viewing specific file formats
- not flexible
- Plotting libraries for viewing statistical results
- struggle with genome scale data
source: software.broadinstitute.org/software/igv/scatterplots
source: datashader.org
def interactive_xy(df, xcol='', ycol='', **kwargs):
# LOTS MORE CODE TO HANDLE OPTIONS
# create the base plot
plot = figure(**kwargs)
# function for image replotting
def create_image(x_range, y_range, w, h):
cvs = ds.Canvas(**kwargs)
agg = cvs.points(df, xcol, ycol)
img = tf.shade(agg, cmap=palette, how=shade_method)
return tf.dynspread(img, threshold=density_threshold, max_px=max_px)
# plot the interactive image
export_image(create_image(x_range, y_range, width, height), 'export')
return InteractiveImage(plot, create_image)
plot = datashade(hv.Points(data, kdims=['position', 'Fst']))
def stack(reads):
cache = {}
for start, stop in reads:
height = 0
searching = True
while searching:
if height in cache:
if start < cache[height]:
height += 1
else:
cache[height] = stop
searching = False
else:
cache[height] = stop
searching = False
yield height
reads = dynspread(datashade(holoviews.Path(read_data))) variants = dynspread(datashade(holoviews.Points(var_data))) reads + variants
reads = dynspread(datashade(holoviews.Path(read_data))) variants = dynspread(datashade(holoviews.Points(var_data))) reads + variants
reads = dynspread(datashade(holoviews.Path(read_data))) variants = dynspread(datashade(holoviews.Points(var_data))) reads + variants + (reads * variants)
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